The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

Abstract

     This research deals with Building A probabilistic Linear programming model  representing, the operation of production in the Middle Refinery Company (Dura, Semawa, Najaif) Considering the demand of each product (Gasoline, Kerosene,Gas Oil, Fuel Oil ).are random variables ,follows certain probability distribution, which are testing by using Statistical programme (Easy fit), thes distribution are found to be Cauchy distribution ,Erlang distribution ,Pareto distribution ,Normal distribution ,and General Extreme value distribution .              &

The current study was conducted for studying the impact of cold plasma on the expression level of three genes that participate in the biosynthesis of the phenylpropanoid pathway in Ocimum basilicum. These studied genes were cinnamate 4-hydroxylase (c4h), 4-coumarate CoA ligase (4cl), and eugenol O-methyl transferase (eomt). Also, the cold plasma impact was studied on the essential oil components and their relation with the gene expression level. The results demonstrated that cold plasma seeds germination of the treated groups 2 (initially for 3 minutes and 3 minutes after 7 days) ,and group 3(initially for 5 minutes and 3 minutes after 7 days)  were faster than the control group. Also, the height average of the mature plants of

The current study aimed to isolate and diagnose Candida spp yeasts that cause candidiasis with a PCR device from patients reviewed for some hospitals in Baghdad city and by 190 samples, the study recorded 123 isolates and the total percentage of infection was 64.7% .Samples were taken from different clinical cases of the vagina, blood and mouth and the Candida spp were (70.37%, 41.26%, 86.95%) respectively. Five types of yeasts were isolated and diagnosed, namely C. albicans, C. tropicalis, C. parapsilosis, C. krusei and C.glabarta. They were confirmed by PCR device and the most notable were yeast C. albicans, where 91 isolates were found, 73.98%, while the lowest infection was recorded. C.glabartawith 3 isolates, at 2.43%, significant diff

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

The paper aims to propose Teaching Learning based Optimization (TLBO) algorithm to solve 3-D packing problem in containers. The objective which can be presented in a mathematical model is optimizing the space usage in a container. Besides the interaction effect between students and teacher, this algorithm also observes the learning process between students in the classroom which does not need any control parameters. Thus, TLBO provides the teachers phase and students phase as its main updating process to find the best solution. More precisely, to validate the algorithm effectiveness, it was implemented in three sample cases. There was small data which had 5 size-types of items with 12 units, medium data which had 10 size-types of items w

This review investigates the practice and influence of chatbots and ChatGPT as employable tools in writing for scientific academic purposes. A primary collection of 150 articles was gathered from academic databases, but it was systematically chosen and refined to include 30 studies that focused on the use of ChatGPT and chatbot technology in academic writing contexts. Chatbots and ChatGPT in writing enhancement, support for student learning at higher education institutions, scientific and medical writing, and the evolution of research and academic publishing are some of the topics covered in the reviewed literature. The review finds these tools helpful, with their greatest advantages being in areas such as structuring writings, gram